Genetic Algorithm for Mulicriteria Optimization of a Multi-Pickup and Delivery Problem with Time Windows

A Genetic Algorithm for the Multi-Pickup and Delivery Problem with time windows

In This paper we present a genetic algorithm for the multi-pickup and delivery problem with time windows (m-PDPTW). The m-PDPTW is an optimization vehicles routing problem which must meet requests for transport between suppliers and customers satisfying precedence, capacity and time constraints. This paper purposes a brief literature review of the PDPTW, present our approach based on genetic algorithms to minimizing the total travel distance and thereafter the total travel cost, by showing that an encoding represents the parameters of each individual.

Memetic Search for Vehicle Routing with Simultaneous Pickup-Delivery and Time Windows

The Vehicle Routing Problem with Simultaneous Pickup-Delivery and Time Windows (VRPSPDTW) has attracted much research interest in the last decade, due to its wide application in modern logistics. Since VRPSPDTW is NP-hard and exact methods are only applicable to small-scale instances, heuristics and meta-heuristics are commonly adopted. In this paper we propose a novel Memetic Algorithm with efficient local search and extended neighborhood, dubbed MATE, to solve this problem. Compared to existing algorithms, the advantages of MATE lie in two aspects. First, it is capable of more effectively ex…

混合记忆搜索算法求解带时间窗、同时取送货及部分充电的电动车路径问题

Hybrid Memetic Search for Electric Vehicle Routing with Time Windows, Simultaneous Pickup-Delivery, and Partial Recharges

针对带时间窗、同时取送货及部分充电的电动车路径问题，提出混合记忆算法，含并行-顺序充电站插入和跨域邻域搜索，并构建大规模真实基准集，实验验证其性能优势。

Un Algorithme génétique pour le problème de ramassage et de livraison avec fenêtres de temps à plusieurs véhicules

The PDPTW is an optimization vehicles routing problem which must meet requests for transport between suppliers and customers satisfying precedence, capacity and time constraints. We present, in this paper, a genetic algorithm for optimization of a multi pickup and delivery problem with time windows (m-PDPTW). We purposes a brief literature review of the PDPTW, present an approach based on genetic algorithms to give a satisfying solution to the m-PDPTW minimizing the total travel cost.

Approche Multicritère pour le Problème de Ramassage et de Livraison avec Fenêtres de Temps à Plusieurs Véhicules

Nowadays, the transport goods problem occupies an important place in the economic life of modern societies. The pickup and delivery problem with time windows (PDPTW) is one of the problems which a large part of the research was interested. In this paper, we present a a brief literature review of the VRP and the PDPTW, propose our multicriteria approach based on genetic algorithms which allows minimize the compromise between the vehicles number, the total tardiness time and the total travel cost. And this, by treating the case where a customer can have multiple suppliers and one supplier can ha…

Few-shots Parallel Algorithm Portfolio Construction via Co-evolution

Generalization, i.e., the ability of solving problem instances that are not available during the system design and development phase, is a critical goal for intelligent systems. A typical way to achieve good generalization is to learn a model from vast data. In the context of heuristic search, such a paradigm could be implemented as configuring the parameters of a parallel algorithm portfolio (PAP) based on a set of training problem instances, which is often referred to as PAP construction. However, compared to traditional machine learning, PAP construction often suffers from the lack of train…